User experience research on social robot application

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wei-Feng Tung ◽  
Jaileez Jara Santiago Campos
Keyword(s):  
User Experience ◽  
System Development ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Fast Detection ◽  
Eeg Data ◽  
The Social ◽  
Intelligent Process

PurposeSocial robot, a subtype of robots that is designed for the various interactive services for human, which must deliver superior user experience (UX) by expressing human-like social behavior or service and emotional sensitivity. This study develops a social robot app called the “Music Buddy” in ASUS Zenbo that provides a situational music based on the users' electroencephalogram (EEG) data. The research uses this app to explore its UX criteria and the prioritization of human robot interaction (HRI).Design/methodology/approachThe research methodologies include the both system development and decision analysis for the social robot. The first part is to design and develop a social robot app. The second part is to investigate the criteria of HRI through the Analytic Hierarchy Process (AHP) from UX aspects.FindingsIn view of the results of the AHP, the first-layer criteria consist of personalized function, easy-to-use the system and intelligent process. In terms of prioritization of multi-criteria, the overall ranking discloses the nine criteria in order including autonomy for robot, easy-to-use EEG device, accurate music preference, simple operations for brainwave device and easy-to-use applications, active music recommendation, automatic updates of music and easy-to-use robot as well as fast detection for emotion.Originality/valueThis research includes a self-developed social robot app and its UX research using AHP. This paper contributes to the improvement and innovation of the social robot design according to the results of UX research on HRI of social robot.

scholarly journals The Fundamental Attribution Error in Human-Robot Interaction: An Experimental Investigation on Attributing Responsibility to a Social Robot for Its Pre-Programmed Behavior

2022 ◽  
Author(s):  
Aike C. Horstmann ◽  
Nicole C. Krämer
Keyword(s):  
Experimental Investigation ◽  
Attribution Theory ◽  
Social Robots ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Fundamental Attribution Error ◽  
Online Study ◽  
The Social ◽  
Attribution Error

AbstractSince social robots are rapidly advancing and thus increasingly entering people’s everyday environments, interactions with robots also progress. For these interactions to be designed and executed successfully, this study considers insights of attribution theory to explore the circumstances under which people attribute responsibility for the robot’s actions to the robot. In an experimental online study with a 2 × 2 × 2 between-subjects design (N = 394), people read a vignette describing the social robot Pepper either as an assistant or a competitor and its feedback, which was either positive or negative during a subsequently executed quiz, to be generated autonomously by the robot or to be pre-programmed by programmers. Results showed that feedback believed to be autonomous leads to more attributed agency, responsibility, and competence to the robot than feedback believed to be pre-programmed. Moreover, the more agency is ascribed to the robot, the better the evaluation of its sociability and the interaction with it. However, only the valence of the feedback affects the evaluation of the robot’s sociability and the interaction with it directly, which points to the occurrence of a fundamental attribution error.

Analysis and monitoring of IoT-assisted human physiological galvanic skin responsefactor for smart e-healthcare

Sensor Review ◽  
2019 ◽  
Vol 39 (4) ◽  
pp. 525-541 ◽  
Author(s):  
Partha Pratim Ray ◽  
Dinesh Dash ◽  
Debashis De
Keyword(s):  
User Experience ◽  
Printed Circuit Board ◽  
System Development ◽  
Flexible Substrate ◽  
Cost Effective ◽  
Circuit Board ◽  
Sensor System ◽  
Case Scenario ◽  
Content Type ◽  
Flexible System

Purpose Background: Every so often, one experiences different physically unstable situations which may lead to possibilities of suffering through vicious physiological risks and extents. Dynamic physiological activities are such a key metric that they are perceived by means of measuring galvanic skin response (GSR). GSR represents impedance of human skin that frequently changes based on different human respiratory and physical instability. Existing solutions, paved in literature and market, focus on the direct measurement of GSR by two sensor-attached leads, which are then parameterized against the standard printed circuit board mechanism. This process is sometimes cumbersome to use, resulting in lower user experience provisioning and adaptability in livelihood activities. The purpose of this study is to validate the novel development of the cost-effective GSR sensing system for affective usage for smart e-healthcare. Design/methodology/approach This paper proposes to design and develop a flexible circuit strip, populated with essential circuitry assemblies, to assess and monitor the level of GSR. Ordinarily, this flexible system would be worn on the back palm of the hand where two leads would contact two sensor strips worn on the first finger. Findings The system was developed on top of Pyralux. Initial goals of this work are to design and validate a flexible film-based GSR system to detect an individual’s level of human physiological activities by acquiring, amplifying and processing GSR data. The measured GSR value is visualized “24 × 7” on a Bluetooth-enabled smartphone via a pre-incorporated application. Conclusion: The proposed sensor-system is capable of raising the qualities such as adaptability, user experience, portability and ubiquity for possible application of monitoring of human psychodynamics in a more cost-effective way, i.e. less than US$50. Practical implications Several novel attributes are envisaged in the development process of the GSR system that made it different from and unique as compared to the existing alternatives. The attributes are as follows: (i) use of reproductive sensor-system fabrication process, (ii) use of flexible-substrate for hosting the system as proof of concept, (iii) use of miniaturized microcontroller, i.e. ATTiny85, (iv) deployment of energy-efficient passive electrical circuitry for noise filtering, (v) possible use case scenario of using CR2032 coin battery for provisioning powering up the system, (vi) provision of incorporation of internet of things (IoT)-cloud integration in existing version while fixing related APIs and (vii) incorporation of heterogeneous software-based solutions to validate and monitor the GSR output such as MakerPlot, Arduino IDE, Fritzing and MIT App Inventor 2. Originality/value This paper is a revised version R1 of the earlier reviewed paper. The proposed paper provides novel knowledge about the flexible sensor system development for GSR monitoring under IoT-based environment for smart e-healthcare.

Design for a Robotic Companion

2015 ◽  
Vol 12 (01) ◽  
pp. 1550007 ◽  
Author(s):  
Jan Kędzierski ◽  
Paweł Kaczmarek ◽  
Michał Dziergwa ◽  
Krzysztof Tchoń
Keyword(s):  
Social Robot ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
University Of Technology ◽  
The Social ◽  
Trial Testing ◽  
History Of ◽  
Human Attitude ◽  
Emotional System ◽  
And Control

We can learn from the history of robotics that robots are getting closer to humans, both in the physical as well as in the social sense. The development line of robotics is marked with the triad: industrial — assistive — social robots, that leads from human–robot separation toward human–robot interaction. A social robot is a robot able to act autonomously and to interact with humans using social cues. A social robot that can assist a human for a longer period of time is called a robotic companion. This paper is devoted to the design and control issues of such a robotic companion, with reference to the robot FLASH designed at the Wroclaw University of Technology within the European project LIREC, and currently developed by the authors. Two HRI experiments with FLASH demonstrate the human attitude toward FLASH. A trial testing of the robot's emotional system is described.

The “Social” of the Socially Interactive Robot: Rethinking Human-Robot Interaction Through Ethnomethodology

2020 ◽  
Author(s):  
Salla Jarske ◽  
Sanna Raudaskoski ◽  
Kirsikka Kaipainen
Keyword(s):  
Social Interaction ◽  
User Experience ◽  
Moral Obligation ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
The Social ◽  
Normative Practice ◽  
Normative Practices

As social robots project socially interactive skills including speech and gestures, they are in a position to project normative practices that humans ordinarily rely upon in their everyday interactions with each other. Social robots enable experiences that are reducible to interaction as a normative practice, such as a sense of moral obligation to respond to a robot’s greeting. This may have consequences both for the user experience and the design of social robots that are currently overlooked. We propose that theoretical-methodological tools from ethnomethodology should be applied to evaluate and investigate the experiences related to social interaction with social robots.

Controlling a Social Robot - Performing Nonverbal Communication through Facial Expressions

2013 ◽  
Vol 837 ◽  
pp. 525-530 ◽  
Author(s):  
Florentina Adăscălitei ◽  
Ioan Doroftei ◽  
Dirk Lefeber ◽  
Bram Vanderborght
Keyword(s):  
Nonverbal Communication ◽  
Facial Expressions ◽  
Degrees Of Freedom ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Basic Emotions ◽  
Face To Face ◽  
The Social ◽  
Emotional Behaviour ◽  
Robot Head

This paper focuses on our primary goal to achieve the emotional behaviour of the new version of the social robot Probo. The ability to enhance nonverbal communication with children is possible through facial expressions, eye-tracking and face-to-face contact. The new social robot has 21 degrees of freedom (DOF), grouped in five subsystems, named generically: eyes, ears, trunk, mouth and neck. The robotic head is actuated using only servo motors and all the components are manufactured using cheap, flexible and easy technologies. In order to get the social robot head able to express emotions, a Graphical User Interface (GUI) was developed. In this way facial expressions are created through sliders or push buttons. Additionally, we investigated the possibility of controlling the robot with an Arduino board. In this case, using pre-programmed or learned algorithms, the robot is getting a semiautonomous level, based on the usage of various sensors, being able to express six basic emotions: happiness, sadness, fear, anger, surprise and disgust. So, based on the feedback provided by the sensors, the robot can react accordingly, enhancing human-robot interaction (HRI).

scholarly journals Music questions in social Q&A: an analysis of Yahoo! Answers

2017 ◽  
Vol 73 (5) ◽  
pp. 992-1009 ◽  
Author(s):  
Morten Hertzum ◽  
Pia Borlund
Keyword(s):  
User Experience ◽  
Information Seeking ◽  
Design Methodology ◽  
Question Type ◽  
Content Type ◽  
User Context ◽  
The Social ◽  
Music Information ◽  
A Site

Purpose Social question and answer (social Q&A) sites have become a popular tool for obtaining music information. The purpose of this paper is to investigate what users ask about, what experience the questions convey, and how users specify their questions. Design/methodology/approach A total of 3,897 music questions from the social Q&A site Yahoo! Answers were categorized according to their question type, user experience, and question specification. Findings The music questions were diverse with (dis)approval (42 percent), factual (21 percent), and advice (15 percent) questions as the most frequent types. Advice questions were the longest and roughly twice as long as (dis)approval and factual questions. The user experience associated with the questions was most often pragmatic (24 percent) or senso-emotional (12 percent). Pragmatic questions were typically about the user’s own performance of music, while senso-emotional questions were about finding music for listening. Notably, half of the questions did not convey information about the user experience but the absence of such information did not reduce the number of answers. In specifying the questions, the most frequent information was about the music context and the user context. Research limitations/implications This study suggests a division of labor between social Q&A sites and search engines for music information retrieval. It should be noted that the study is restricted to one social Q&A site. Originality/value Social Q&A sites provide an opportunity for studying what information real users seek about music and what information they specify to retrieve it, thereby elucidating the role of social Q&A in music information seeking.

How many facets does a “social robot” have? A review of scientific and popular definitions online

2019 ◽  
Vol 33 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Mauro Sarrica ◽  
Sonia Brondi ◽  
Leopoldina Fortunati
Keyword(s):  
Scientific Literature ◽  
Social Representations ◽  
Social Robots ◽  
Social Robot ◽  
Data Sets ◽  
Content Type ◽  
The Public ◽  
Online Tools ◽  
The Social ◽  
The Public Sphere

Purpose On the verge of what has been hailed as the next technological revolution, the purpose of this paper is to examine scientific and popular definitions of the social robot, reflecting on how expert and lay spheres of knowledge interact. Drawing on social representations theory, this paper aims to elucidate how social robots are named and classified, and to examine the dynamics contributing to their definition. Design/methodology/approach Scientific and popular definitions of the social robot were investigated by conducting: a systematic review of relevant articles published from 2009 to 2015 in the International Journal of Social Robotics; an analysis of the definitions retrievable from the scientific literature using Google Scholar; and an assessment of the interest in the public sphere, and of the popular definitions retrievable online (by inputting “social robot” in Google Trends, and in Google). Findings Scientific definitions of the social robot adopt two strategies, one drawing on and merging previous definitions, the other proposing new, visionary, forward-looking definitions. Popular online definitions of social robots attribute new emotional, linguistic and social capabilities to their physical body. Research limitations/implications The findings need to be confirmed by further research, given the limited size of the data sets considered, and the distortions in the data due to filters and the opacity of the online tools employed. Originality/value Both scientific and non-scientific definitions see social robots as being capable of interacting with and working for humans, but attribute them a different degree of (functional or full) autonomy. In future, any controversy over the connotation of social robots is likely to concern their sociality and autonomy rather than their functionality.

scholarly journals Promises and partnership in human-robot interaction

2021 ◽  
Author(s):  
Lorenzo Cominelli ◽  
Francesco Feri ◽  
Roberto Garofolo ◽  
Caterina GIANNETTI ◽  
Miguel A.MELENDEZ-JIMENEZ ◽  
...  
Keyword(s):  
Electrodermal Activity ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Trust Game ◽  
Emotional States ◽  
Human Beings ◽  
Robot Interaction ◽  
Intelligent Machines ◽  
The Social ◽  
Psychophysiological Arousal

Abstract Understanding human trust in machine partners has become imperative due to the widespread use of intelligent machines in a variety of applications and contexts. The aim of this paper is to investigate whether human-beings trust a social robot - i.e. a human-like robot that embodies emotional states, empathy, and non-verbal communication - differently than other types of agents. To do so, we adapt the well-known economic trust-game proposed by Charness and Dufwenberg (2006) to assess whether receiving a promise from a robot increases human-trust in it. We find that receiving a promise from the robot increases the trust of the human in it, but only for individuals who perceive the robot very similar to a human-being. Importantly, we observe a similar pattern in choices when we replace the humanoid counterpart with a real human but not when it is replaced by a computer-box. Additionally, we investigate participants' psychophysiological reaction in terms of cardiovascular and electrodermal activity. Our results highlight an increased psychophysiological arousal when the game is played with the social robot compared to the computer-box. Taken all together, these results strongly support the development of technologies enhancing the humanity of robots.

Shall I trust you? From child human-robot interaction to trusting relationships

2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  
Keyword(s):  
Behavioral Pattern ◽  
Human Robot Interaction ◽  
School Age Children ◽  
Social Relevance ◽  
Robot Interaction ◽  
Cognitive Correlates ◽  
The Social ◽  
The Relationship

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.

A chronology of Distributed Adaptive Control

2018 ◽  
Author(s):  
Paul F. M. J. Verschure
Keyword(s):  
Adaptive Control ◽  
Human Robot Interaction ◽  
Integration Framework ◽  
The Social ◽  
Distributed Adaptive Control ◽  
Core Components ◽  
Mind And Brain ◽  
Convergent Validation ◽  
The Mind ◽  
And Behavior

This chapter presents the Distributed Adaptive Control (DAC) theory of the mind and brain of living machines. DAC provides an explanatory framework for biological brains and an integration framework for synthetic ones. DAC builds on several themes presented in the handbook: it integrates different perspectives on mind and brain, exemplifies the synthetic method in understanding living machines, answers well-defined constraints faced by living machines, and provides a route for the convergent validation of anatomy, physiology, and behavior in our explanation of biological living machines. DAC addresses the fundamental question of how a living machine can obtain, retain, and express valid knowledge of its world. We look at the core components of DAC, specific benchmarks derived from the engagement with the physical and the social world (the H4W and the H5W problems) in foraging and human–robot interaction tasks. Lastly we address how DAC targets the UTEM benchmark and the relation with contemporary developments in AI.

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